Modern data centers often have a multi-tier configuration wherein a front end server accesses one or more layers of middle-tier and back-tier servers for various services. One example of a back-end server is a storage array. Storage arrays form the backbone of modern data centers by providing consolidated data access to multiple applications simultaneously. Increasingly, organizations are moving towards consolidated storage, either using block-based access over a Storage Area Network (SAN) or file-based access over Network-Attached Storage (NAS) systems. A Storage Area Network is a network whose primary purpose is the transfer of data between computer systems and storage elements. Easy access from anywhere at anytime, ease of backup, flexibility in allocation and centralized administration are some of the advantages of storage arrays.
Quality of Service (QoS) refers to resource management methodologies whereby resources are allocated among a plurality of users or clients according to a policy. The policy may guarantee a minimum and/or maximum level of service (e.g., as a percentage of resources), or it may set limits and reservations which are expressed in absolute units, such as MHz or GHz for CPU resource allocation, GB for memory or disk resource allocation, and Mbps or Gbps for network bandwidth resource allocation. A “limit” is a maximum level of service expressed in terms of absolute units and a “reservation” is a minimum level of service expressed in terms of absolute units. It is also common to distribute services according to assigned resource “shares” (also known as “weights”) so that each client is provided a level of service that compares to its peers at the same ratio as the assigned shares. In addition, combinations of these policies are possible. Thus, QoS suggests an ability to evenly distribute services or arbitrarily assign priority to selected applications, users, or data flows. QoS management, however, may be complicated when a client that is not bound by a QoS policy accesses a shared resource. Such client may consume services at a rate that impacts the level of service received by the clients that are bound by the QoS policy. In some situations referred to herein as an “anomaly,” the workload presented by the client not bound by the QoS policy is so large that it interferes with the proper distribution of resources, such as IO access bandwidth, to clients in accordance with the QoS policy.